Various systems exist for providing services to users. Many of such systems deploy resources to facilitate the services. The resources may be dynamic in the sense that the availability, number, and deployment timeframes of the resources may change over time and/or in service areas.
Generally, a system may consider the demand for a particular service in a service area. The service area may be divided into multiple clusters. The system attempts to allocate the resources to the clusters by balancing the availability, number, and deployment timeframes of the resources against the demand. However, many technical challenges exist and can result in sub-optimal utilization of the resource or, in certain situations, a failure to meet the demand.
Some of the technical challenges relate to searching for the optimal balance. For example, if the resources are allocated favorably to a particular set of clusters, the demand in the remaining clusters may be underserved. Conversely, if the resources are uniformly distributed across the clusters, a high-demand cluster may be underserved, while a low-demand cluster may be overserved and allocated resources may sit idle. Hence, one existing approach to deal with an uneven demand distribution may allocate the resources based on specific distribution in each cluster.
However, even with this approach, many technical challenges remain when the demand is also dynamic. More particularly, the demand for the service in each cluster may be random and, thus, may change over time. Unless the allocation of the dynamic resources is updated over time to re-balance against the dynamic demand for a holistic redistribution across the clusters, the demand may not be properly met and the resources may be inefficiently utilized. On the other hand, if some sort of redistribution is performed, the redistribution results in additional technical challenges. One additional technical challenge relates to the number of times a resource is re-allocated. Specifically, any time the resource is redistributed from one cluster to another cluster, a down time arises during which the resource may not be usable to facilitate the service. Thus, a high frequency of re-allocation may translate into a long down time and, thus, inefficient utilization of the resource. Another additional technical challenge relates to providing information about the redistribution. Specifically, the system should transmit notifications to client devices about the redistributions. If too many notifications are transmitted, network bandwidth and computing resource usage may be wasted. Conversely, if too little notifications are transmitted, certain responses from the client devices may not be timely and, accordingly, the service may not be timely facilitated to certain users. In both examples, the notification scheme may impact how well the demand is met.